Automation at Sea and Human Factors

Linda Grosser, Chelsea Wilkinson, Michelle Oppert, Siobhan Banks, Benoit Clement

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)
2 Downloads (Pure)

Abstract

Collisions at sea can have severe effects for humans and the environment, leading to costs for marine organisations. Human factors, particularly fatigue, contribute to more than 80% of maritime collisions. Ships and vessels have become increasingly sophisticated in design and more recently, autonomous navigation systems have been integrated to reduce human errors associated with collisions. The rise in maritime traffic makes these autonomous systems crucial for enhancing safety. A challenge for autonomous navigation systems, causing contention among mariners and within maritime literature, is compliance with COLREG (Convention on the International Regulations for Preventing Collisions at Sea). An emerging solution to this challenge involves the development of a light simulator (COLSim) that leverages historical AIS (Automatic Identification System) data to introduce multiple autonomous vehicles into real-world scenarios, while incorporating the COLREG rules to avoid collision. Acceptance of autonomous navigation systems is important for the future of transportation at sea and is the natural evolution of maritime traffic. As AI is still evolving, humans will continue to play a vital role in the operation of ships and vessels and interpretation of COLREGs. In the future, human-AI interactions will be important for work, health, and organisational safety, where both humans and AI can support each other. Finding a balance between human expertise and AI assistance is essential for the maritime industry's future safety and efficiency.

Original languageEnglish
Pages (from-to)301-306
Number of pages6
JournalIFAC-PapersOnLine
Volume58
Issue number20
DOIs
Publication statusPublished - 2024
Externally publishedYes
Event15th IFAC Conference on Control Applications in Marine Systems, Robotics and Vehicles, CAMS 2024 - Blacksburg, United States
Duration: 3 Sept 20245 Sept 2024

Keywords

  • COLREGs
  • human factors
  • human-AI interaction
  • machine learning
  • simulation

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